Outcomes and Patient Satisfaction of a Safety-Net Protocol of Portable Sleep Monitoring for Diagnosis of Obstructive Sleep Apnea

CHEST Journal ◽  
2010 ◽  
Vol 138 (4) ◽  
pp. 627A
Author(s):  
Richard S. Tejedor ◽  
Ibrahim El-Abbassi
Keyword(s):  
Obstructive Sleep Apnea ◽  
Patient Satisfaction ◽  
Sleep Apnea ◽  
Safety Net ◽  
Sleep Monitoring ◽  
Obstructive Sleep ◽  
Portable Sleep Monitoring

scholarly journals Diagnostic accuracy and feasibility of portable sleep monitoring in patients with obstructive sleep apnea: Re-exploring the utility in the current COVID-19 pandemic

2021 ◽  
Author(s):  
Mansi Gupta ◽  
Pranav Ish ◽  
Shibdas Chakrabarti ◽  
Manas Kamal Sen ◽  
Prabhakar Mishra ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Diagnostic Accuracy ◽  
Type I ◽  
Care Hospital ◽  
Sleep Monitoring ◽  
High Burden ◽  
Sleep Studies ◽  
Obstructive Sleep ◽  
Portable Sleep Monitoring

Portable sleep monitoring (PSM) is a promising alternative diagnostic tool for Obstructive Sleep Apnea (OSA) especially in high burden resource limited settings. We aimed to determine the diagnostic accuracy and feasibility of PSM device-based studies in patients presenting for evaluation of OSA at a tertiary care hospital in North-India. PSM studies (using a Type-III PSM device) were compared for technical reliability and diagnostic accuracy with the standard laboratory-based Type-I polysomnography (PSG). Patients were also interviewed about their experience on undergoing an unsupervised PSM studies. Fifty patients (68% males) were enrolled in the study, of which only 30% patients expressed their concerns about undergoing unsupervised PSM studies which included safety issues, ease of use, diagnostic accuracy, etc. Technical acceptability criteria were easily met by the PSM studies with signal loss in 12% studies (complete data loss and inaccessible data in 6% studies), warranting repetition sleep studies in four patients. The overall sensitivity of PSM device (AHI ≥5) was 93.5% (area under curve; AUC: 0.87). The diagnostic accuracy was 68.5%, 80%, and 91.4% for mild, moderate, and severe cases of OSA, respectively. An overall strong correlation was observed between PSM-AHI (apnoea-hypopnoea index) and PSG (r>0.85, p≤0.001), especially in severe OSA. The observed sensitivity was >90% for AHI>20 (clinically significant OSA), with high specificity of 91% for severe OSA (AUC: 0.94, 0.97 for AHI>20, AHI>30 respectively). The overall Bland-Altman concordance analysis also demonstrated only a small dispersion for PSM studies with a Cronbach’s coefficient of 0.95. Therefore, there is good diagnostic accuracy as well as feasibility of home-based portable sleep studies in Indian patients. It can be promoted for widespread use in high burden countries like India for diagnosing and managing appropriately selected stable patients with high clinical probability of OSA, especially during the ongoing crises of COVID-19 pandemic.

scholarly journals 0576 Validation of the Contact-free Sleep Monitoring Device for Diagnosis of Obstructive Sleep Apnea in Chinese Adults

SLEEP ◽  
2019 ◽  
Vol 42 (Supplement_1) ◽  
pp. A229-A229
Author(s):  
Xiaosong Dong ◽  
Hui Zhi ◽  
Jianan Chen ◽  
Fang Han ◽  
Rui Zhao
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Monitoring Device ◽  
Chinese Adults ◽  
Sleep Monitoring ◽  
Obstructive Sleep ◽  
Contact Free

scholarly journals Doppler Radar-Based Non-Contact Health Monitoring for Obstructive Sleep Apnea Diagnosis: A Comprehensive Review

2019 ◽  
Vol 3 (1) ◽  
pp. 3 ◽  
Author(s):  
Vinh Phuc Tran ◽  
Adel Ali Al-Jumaily ◽  
Syed Mohammed Shamsul Islam
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Doppler Radar ◽  
Future Research ◽  
Physical And Mental Health ◽  
Sleep Monitoring ◽  
Comprehensive Review ◽  
Limited Mobility ◽  
Obstructive Sleep ◽  
Cardio Vascular

Today’s rapid growth of elderly populations and aging problems coupled with the prevalence of obstructive sleep apnea (OSA) and other health related issues have affected many aspects of society. This has led to high demands for a more robust healthcare monitoring, diagnosing and treatments facilities. In particular to Sleep Medicine, sleep has a key role to play in both physical and mental health. The quality and duration of sleep have a direct and significant impact on people’s learning, memory, metabolism, weight, safety, mood, cardio-vascular health, diseases, and immune system function. The gold-standard for OSA diagnosis is the overnight sleep monitoring system using polysomnography (PSG). However, despite the quality and reliability of the PSG system, it is not well suited for long-term continuous usage due to limited mobility as well as causing possible irritation, distress, and discomfort to patients during the monitoring process. These limitations have led to stronger demands for non-contact sleep monitoring systems. The aim of this paper is to provide a comprehensive review of the current state of non-contact Doppler radar sleep monitoring technology and provide an outline of current challenges and make recommendations on future research directions to practically realize and commercialize the technology for everyday usage.

scholarly journals Oral Appliance Effectiveness and Patient Satisfaction with Obstructive Sleep Apnea Treatment in Adults

2019 ◽  
Vol 25 ◽  
pp. 516-524
Author(s):  
Marketa Skalna ◽  
Vilen Novak ◽  
Marek Buzga ◽  
Pavel Skalny ◽  
Jaroslava Hybaskova ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Patient Satisfaction ◽  
Sleep Apnea ◽  
Oral Appliance ◽  
Obstructive Sleep ◽  
Sleep Apnea Treatment

scholarly journals Validation of a novel sleep-monitoring system for diagnosing obstructive sleep apnea: A comparison with polysomnography

2016 ◽  
Vol 12 (5) ◽  
pp. 2937-2941 ◽  
Author(s):  
Lili Meng ◽  
Huajun Xu ◽  
Jian Guan ◽  
Hongliang Yi ◽  
Hongmin Wu ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Monitoring System ◽  
Sleep Monitoring ◽  
Obstructive Sleep

scholarly journals Automatic Home-based Screening of Obstructive Sleep Apnea using Single Channel Electrocardiogram and SPO2 Signals

2021 ◽  
Vol 12 (06) ◽  
pp. 47-63
Author(s):  
Hosna Ghandeharioun
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Closed Loop ◽  
Single Channel ◽  
Upper Airway ◽  
Sleep Monitoring ◽  
Combination Methods ◽  
Home Based ◽  
Obstructive Sleep ◽  
On Line

Obstructive sleep apnea (OSA) is one of the most widespread respiratory diseases today. Complete or relative breathing cessations due to upper airway subsidence during sleep is OSA. It has confirmed potential influence on Covid-19 hospitalization and mortality, and is strongly associated with major comorbidities of severe Covid-19 infection. Un-diagnosed OSA may also lead to a variety of severe physical and mental side-effects. To score OSA severity, nocturnal sleep monitoring is performed under defined protocols and standards called polysomnography (PSG). This method is time-consuming, expensive, and requiring professional sleep technicians. Automatic home-based detection of OSA is welcome and in great demand. It is a fast and effective way for referring OSA suspects to sleep clinics for further monitoring. On-line OSA detection also can be a part of a closed-loop automatic control of the OSA therapeutic/assistive devices. In this paper, several solutions for online OSA detection are introduced and tested on 155 subjects of three different databases. The best combinational solution uses mutual information (MI) analysis for selecting out of ECG and SpO2-based features. Several methods of supervised and unsupervised machine learning are employed to detect apnoeic episodes. To achieve the best performance, the most successful classifiers in four different ternary combination methods are used. The proposed configurations exploit limited use of biological signals, have online working scheme, and exhibit uniform and acceptable performance (over 85%) in all the employed databases. The benefits have not been gathered all together in the previous published methods.

scholarly journals 1197 Utility of Fitbit Charge 2 for Sleep Monitoring in Patients With Obstructive Sleep Apnea

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A458-A458
Author(s):  
D Kim ◽  
W Shin ◽  
J Byun
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Total Sleep Time ◽  
Sleep Stage ◽  
Sleep Time ◽  
Wearable Devices ◽  
Sleep Stages ◽  
Sleep Monitoring ◽  
Obstructive Sleep ◽  
Single Center Observational Study

Abstract Introduction The wearable device may be useful in monitoring sleep. Many studies reported reliable data in detecting sleep-wake states and sleep stage proportion in healthy adults, However, only a few validation studies were performed evaluating sleep using the wearable devices in patients with obstructive sleep apnea(OSA), which showed insufficient accuracy. We aimed to evaluate the reliability of multi-sensory wristband (Fitbit Charge 2) in patients with OSA. Methods This was a preliminary analysis of a prospective single-center observational study. Consecutive patients underwent standard Polysomnography (PSG) for evaluation of OSA with Fitbit Charge 2. Sleep data from PSG and Fitbit charge 2 were compared using paired t-tests and Bland-Altman plots. Results A total of eighty-six patients were analyzed. Four of them had poor data quality, 18 of them did not show sleep stages. Compared with the PSG, Fitbit Charge 2 showed higher total sleep time (419.1±194.0 vs 269.8±22.6, p<0.001) and sleep efficiency (95.8±2.5 vs 84.6±7.1, p<0.001). Those with sleep stage data showed higher sleep efficacy (87.7±5.5 vs 82.37.5, p=0.024) and a lower proportion of N1 sleep (33.7±19.9 vs 65.3±38.8, p=0.01). Conclusion Fitbit Charge 2 showed limited utility in monitoring sleep in patients with obstructive sleep apnea. Support none

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